18 citations · 40 across the 16 of their papers we have counts for
17 papers
One-bit Compressed Sensing using Generative Models
Swatantra Kafle, Geethu Joseph, Pramod K. Varshney
This paper addresses the classical problem of one-bit compressed sensing using a deep learning-based reconstruction algorithm that leverages a trained generative model to enhance t…
Sparse Actuator Scheduling for Discrete-Time Linear Dynamical Systems
Krishna Praveen V. S. Kondapi, Chandrasekhar Sriram, Geethu Joseph +1
We consider the control of discrete-time linear dynamical systems using sparse inputs where we limit the number of active actuators at every time step. We develop an algorithm for…
Joint State and Sparse Input Estimation in Linear Dynamical Systems
Rupam Kalyan Chakraborty, Geethu Joseph, Chandra R. Murthy
Sparsity constraints on the control inputs of a linear dynamical system naturally arise in several practical applications such as networked control, computer vision, seismic signal…
Anomaly Detection via Learning-Based Sequential Controlled Sensing
Geethu Joseph, Chen Zhong, M. Cenk Gursoy +2
In this paper, we address the problem of detecting anomalies among a given set of binary processes via learning-based controlled sensing. Each process is parameterized by a binary…
Bayesian Algorithms for Kronecker-structured Sparse Vector Recovery With Application to IRS-MIMO Channel Estimation
Yanbin He, Geethu Joseph
We study the sparse recovery problem with an underdetermined linear system characterized by a Kronecker-structured dictionary and a Kronecker-supported sparse vector. We cast this…
Structure-aware Sparse Bayesian Learning-based Channel Estimation for Intelligent Reflecting Surface-aided MIMO
Yanbin He, Geethu Joseph
This paper presents novel cascaded channel estimation techniques for an intelligent reflecting surface-aided multiple-input multiple-output system. Motivated by the channel angular…